{"id":"https://openalex.org/W3083159507","doi":"https://doi.org/10.1145/3409256.3409812","title":"Unbiased Pairwise Learning from Biased Implicit Feedback","display_name":"Unbiased Pairwise Learning from Biased Implicit Feedback","publication_year":2020,"publication_date":"2020-09-05","ids":{"openalex":"https://openalex.org/W3083159507","doi":"https://doi.org/10.1145/3409256.3409812","mag":"3083159507"},"language":"en","primary_location":{"id":"doi:10.1145/3409256.3409812","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3409256.3409812","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 ACM SIGIR on International Conference on Theory of Information Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101991694","display_name":"Yuta Saito","orcid":"https://orcid.org/0000-0003-4357-5835"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yuta Saito","raw_affiliation_strings":["Tokyo Institute of Technology, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I114531698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101991694"],"corresponding_institution_ids":["https://openalex.org/I114531698"],"apc_list":null,"apc_paid":null,"fwci":6.4058,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.9678194,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.98580002784729,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9822999835014343,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.7979645729064941},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6619226336479187},{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.6382521986961365},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6095600128173828},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5862360000610352},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.516544759273529},{"id":"https://openalex.org/keywords/ideal","display_name":"Ideal (ethics)","score":0.4939575791358948},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4495571255683899},{"id":"https://openalex.org/keywords/relevance-feedback","display_name":"Relevance feedback","score":0.44232290983200073},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4305621087551117},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.4300772249698639},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.4272730350494385},{"id":"https://openalex.org/keywords/bias-of-an-estimator","display_name":"Bias of an estimator","score":0.42400574684143066},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40267789363861084},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3679134249687195},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3545230031013489},{"id":"https://openalex.org/keywords/minimum-variance-unbiased-estimator","display_name":"Minimum-variance unbiased estimator","score":0.2723901569843292},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2575500011444092},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.24252945184707642},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10045555233955383},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.08090895414352417}],"concepts":[{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.7979645729064941},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6619226336479187},{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.6382521986961365},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6095600128173828},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5862360000610352},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.516544759273529},{"id":"https://openalex.org/C2776639384","wikidata":"https://www.wikidata.org/wiki/Q840396","display_name":"Ideal (ethics)","level":2,"score":0.4939575791358948},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4495571255683899},{"id":"https://openalex.org/C2779532271","wikidata":"https://www.wikidata.org/wiki/Q445558","display_name":"Relevance feedback","level":4,"score":0.44232290983200073},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4305621087551117},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.4300772249698639},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.4272730350494385},{"id":"https://openalex.org/C191393472","wikidata":"https://www.wikidata.org/wiki/Q15222032","display_name":"Bias of an estimator","level":4,"score":0.42400574684143066},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40267789363861084},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3679134249687195},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3545230031013489},{"id":"https://openalex.org/C165646398","wikidata":"https://www.wikidata.org/wiki/Q3755281","display_name":"Minimum-variance unbiased estimator","level":3,"score":0.2723901569843292},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2575500011444092},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.24252945184707642},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10045555233955383},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.08090895414352417},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3409256.3409812","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3409256.3409812","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 ACM SIGIR on International Conference on Theory of Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1886704267","https://openalex.org/W1992665562","https://openalex.org/W2101409192","https://openalex.org/W2113640060","https://openalex.org/W2132917208","https://openalex.org/W2150291618","https://openalex.org/W2507134384","https://openalex.org/W2741497758","https://openalex.org/W2769473018","https://openalex.org/W2887133760","https://openalex.org/W2891520095","https://openalex.org/W2892888989","https://openalex.org/W2908074993","https://openalex.org/W2949676527","https://openalex.org/W2963465723","https://openalex.org/W2998534896","https://openalex.org/W3150893739"],"related_works":["https://openalex.org/W143502885","https://openalex.org/W42113618","https://openalex.org/W2103468410","https://openalex.org/W2480115405","https://openalex.org/W3197542402","https://openalex.org/W1856228368","https://openalex.org/W2971527398","https://openalex.org/W2767338541","https://openalex.org/W2606864227","https://openalex.org/W2429267751"],"abstract_inverted_index":{"Implicit":[0],"feedback":[1,22,45,52,159],"is":[2,8,24,46,56,69,95,169],"prevalent":[3],"in":[4,11,156,178],"real-world":[5,206],"scenarios":[6],"and":[7,38,140,165,197],"widely":[9],"used":[10,121],"the":[12,18,43,82,114,124,152,166,170,188,193,209],"construction":[13],"of":[14,20,65,86,192,212],"recommender":[15],"systems.":[16],"However,":[17],"application":[19],"implicit":[21,158],"data":[23],"much":[25],"more":[26],"complicated":[27],"than":[28,60],"its":[29],"explicit":[30],"counterpart":[31],"because":[32],"it":[33],"provides":[34],"only":[35],"positive":[36,47,51],"feedback,":[37],"we":[39,104,128,186],"cannot":[40],"know":[41],"whether":[42],"non-interacted":[44],"or":[48,88],"negative.":[49],"Furthermore,":[50],"for":[53,97,135,174],"rare":[54,67],"items":[55,68],"observed":[57],"less":[58],"frequently":[59],"popular":[61],"items.":[62],"The":[63],"relevance":[64,116],"such":[66,75],"often":[70],"underestimated.":[71],"Existing":[72],"solutions":[73],"to":[74,79,122,162],"challenges":[76,177],"are":[77],"subject":[78],"bias":[80],"toward":[81],"ideal":[83,108,137],"loss":[84,110,139],"function":[85,111],"interest":[87],"accept":[89],"a":[90,98,130,141,179,198],"simple":[91],"pointwise":[92],"approach,":[93],"which":[94],"inappropriate":[96],"ranking":[99,125],"task.":[100],"In":[101],"this":[102,136],"study,":[103],"first":[105,171],"define":[106],"an":[107],"pairwise":[109,138,149,172],"defined":[112],"using":[113,157,205],"ground-truth":[115],"parameters":[117],"that":[118],"should":[119],"be":[120,163],"optimize":[123],"metrics.":[126],"Subsequently,":[127],"propose":[129],"theoretically":[131,180],"grounded":[132],"unbiased":[133,195],"estimator":[134,196],"corresponding":[142],"algorithm,":[143],"Unbiased":[144],"Bayesian":[145],"Personalized":[146],"Ranking.":[147],"A":[148],"algorithm":[150,168],"addressing":[151],"two":[153],"major":[154],"difficulties":[155],"has":[160],"yet":[161],"investigated,":[164],"proposed":[167,194],"method":[173],"solving":[175],"these":[176],"principal":[181],"manner.":[182],"Through":[183],"theoretical":[184],"analysis,":[185],"provide":[187],"critical":[189],"statistical":[190],"properties":[191],"practical":[199,210],"variance":[200],"reduction":[201],"technique.":[202],"Empirical":[203],"evaluations":[204],"datasets":[207],"demonstrate":[208],"strength":[211],"our":[213],"approach.":[214]},"counts_by_year":[{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
